DataFrame Query Rounding Error

[wisefool769]

Code Sample, a copy-pastable example if possible

import pandas as pd

df = pd.DataFrame([{"A": 1000000000.0099}])
cutoff = 1000000000.006

local_res = "works" if df.query("A < @cutoff").empty else "fails"
print("query by local var %s" % local_res)

explicit_res = "works" if df.query("A < %.3f" % cutoff).empty else "fails"
print("explicit query %s" % explicit_res)

Expected Output

query by local var works
explicit query fails

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.2.0-42-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 20.3
Cython: 0.23.4
numpy: 1.11.1
scipy: 0.18.0
statsmodels: 0.6.1
xarray: None
IPython: 5.0.0
sphinx: 1.3.5
patsy: 0.4.1
dateutil: 2.5.1
pytz: 2016.2
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext)
jinja2: 2.8
boto: 2.39.0
pandas_datareader: None

[chris-b1]

Yeah, something going wrong here - most likely the literal being cast to a 32 bit float. Doesn't seem to be a numexpr bug, and works correctly on python 3, PRs welcome!

import numexpr as ne
a, b = 1000000000.0099, 1000000000.006

ne.evaluate('a < %.3f' % b)
Out[57]: array(False, dtype=bool)

pd.eval("a <  %.3f" % b)
Out[58]: True